Libraries

# SPDS
library(tidyverse)
library(sf)
library(units)

# Data
library(USAboundaries)
library(rnaturalearth)

# Visualization
library(gghighlight)
library(ggrepel)
library(knitr)

Question 1

# 1.1 - Define a Projection

eqdc = '+proj=eqdc +lat_0=40 +lon_0=-96 +lat_1=20 +lat_2=60 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs'

# 1.2 - Get USA state boundaries

conus = USAboundaries::us_states(resolution = "low") %>% 
  filter(!name %in% c("Alaska", "Hawaii", "Puerto Rico")) %>% 
  st_transform(eqdc)

# 1.3 - Get country boundaries for Mexico, the United States of America, and Canada

desired_boundaries = rnaturalearth::countries110 %>% 
  st_as_sf() %>% 
  filter(admin %in% c("Mexico", "United States of America", "Canada")) %>% 
  st_transform(eqdc)

# 1.4 - Get city locations from the CSV file

cities = read.csv("../data/uscities.csv") %>% 
  st_as_sf(coords = c("lng", "lat"), crs = 4326) %>% 
  filter(!state_name %in% c("Alaska", "Hawaii", "Puerto Rico")) %>% 
  st_transform(eqdc)

Question 2

# 2.1 - Distance to USA border

union_conus = st_union(conus) %>% 
  st_cast("MULTILINESTRING")

cities_dist_USA = cities

cities_dist_USA = mutate(cities_dist_USA,
                         border_dist = st_distance(cities_dist_USA, union_conus),
                         border_dist = units::set_units(border_dist, "km"),
                         border_dist = drop_units(border_dist))

top5_USA = cities_dist_USA %>% 
  select(city, state_name, border_dist) %>% 
  slice_max(border_dist, n = 5) %>% 
  st_drop_geometry()

knitr::kable(top5_USA, caption = "Cities Farthest from US Border",
             col.names = c("City",
                           "State",
                           "Distance from Border in km"))
Cities Farthest from US Border
City State Distance from Border in km
Dresden Kansas 1012.398
Herndon Kansas 1007.763
Hill City Kansas 1005.143
Atwood Kansas 1004.754
Jennings Kansas 1003.646 
# 2.2 - Distance to states

conus_states = st_combine(conus) %>% 
  st_cast("MULTILINESTRING")

cities_dist_states = cities

cities_dist_states = mutate(cities_dist_states,
                            states_dist = st_distance(cities_dist_states, conus_states),
                            states_dist = units::set_units(states_dist, "km"),
                            states_dist = drop_units(states_dist))

top5_states = cities_dist_states %>% 
  select(city, state_name, states_dist) %>% 
  slice_max(states_dist, n = 5) %>% 
  st_drop_geometry()

knitr::kable(top5_states, caption = "Cities Farthest from its State Border",
             col.names = c("City",
                           "State",
                           "Distance from State Border in km"))
Cities Farthest from its State Border
City State Distance from State Border in km
Lampasas Texas 308.9216
Kempner Texas 302.5912
Bertram Texas 302.5703
Harker Heights Texas 298.8125
Florence Texas 298.6804 
# 2.3 - Distance to Mexico

mexico = desired_boundaries %>% 
  filter(admin %in% c("Mexico")) %>% 
  st_cast("MULTILINESTRING")

cities_dist_mexico = cities

cities_dist_mexico = mutate(cities_dist_mexico,
                            mexico_dist = st_distance(cities_dist_mexico, mexico),
                            mexico_dist = units::set_units(mexico_dist, "km"),
                            mexico_dist = drop_units(mexico_dist))

top5_mexico = cities_dist_mexico %>% 
  select(city, state_name, mexico_dist) %>% 
  slice_max(mexico_dist, n = 5) %>% 
  st_drop_geometry()
  
knitr::kable(top5_mexico, caption = "Cities Farthest from Mexico Border",
             col.names = c("City",
                           "State",
                           "Distance from Mexico Border in km"))
Cities Farthest from Mexico Border
City State Distance from Mexico Border in km
Caribou Maine 3250.334
Presque Isle Maine 3234.570
Calais Maine 3134.348
Passamaquoddy Pleasant Point Maine 3127.869
Eastport Maine 3125.624 
# 2.4 - Distance to Canada

canada = desired_boundaries %>% 
  filter(admin %in% c("Canada")) %>% 
  st_cast("MULTILINESTRING")

cities_dist_canada = cities

cities_dist_canada = mutate(cities_dist_canada,
                            canada_dist = st_distance(cities_dist_canada, canada),
                            canada_dist = units::set_units(canada_dist, "km"),
                            canada_dist = drop_units(canada_dist))

top5_canada = cities_dist_canada %>% 
  select(city, state_name, canada_dist) %>% 
  slice_max(canada_dist, n = 5) %>% 
  st_drop_geometry()
  
knitr::kable(top5_canada, caption = "Cities Farthest from Canada Border",
             col.names = c("City",
                           "State",
                           "Distance from Canada Border in km"))
Cities Farthest from Canada Border
City State Distance from Canada Border in km
Guadalupe Guerra Texas 2206.455
Fronton Texas 2204.790
Fronton Ranchettes Texas 2202.118
Evergreen Texas 2202.020
Ramos Texas 2201.882

Question 3

# 3.1 - Data

cities_10 = cities %>% 
  slice_max(population, n = 10)

ggplot() +
  geom_sf(data = desired_boundaries, color = "grey40") +
  geom_sf(data = conus, color = "black") +
  geom_sf(data = cities_10, color = "blue4") +
  ggrepel::geom_label_repel(
    data = cities_10,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "10 Largest US Cities by Population") + 
  ggthemes::theme_map() 

# 3.2 - City distance from border

top5_USA_geom = slice_max(cities_dist_USA, border_dist, n = 5)

ggplot() +
  geom_sf(data = union_conus, color = "black") +
  geom_sf(data = cities_dist_USA, aes(color = as.numeric(border_dist)), size = 0.1) +
  geom_sf(data = top5_USA_geom, color = "grey40") +
  scale_color_gradient(low = "blue", high = "red") +
  ggrepel::geom_label_repel(
    data = top5_USA_geom,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Cities Farthest from US Border",
       color = "Distance in km") + 
  ggthemes::theme_map() 

# 3.3 - City distance from nearest state

top5_states_geom = slice_max(cities_dist_states, states_dist, n = 5)

ggplot() +
  geom_sf(data = conus_states, color = "black") +
  geom_sf(data = cities_dist_states, aes(color = as.numeric(states_dist)), size = 0.1) +
  geom_sf(data = top5_states_geom, color = "grey40") +
  scale_color_gradient(low = "blue", high = "red") +
  ggrepel::geom_label_repel(
    data = top5_states_geom,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Cities Farthest from US Border",
       color = "Distance in km") + 
  ggthemes::theme_map()

# 3.4 - Equidistant boundary from Mexico to Canada

cities_dist_eq = st_join(cities_dist_mexico, cities_dist_canada, by = "city") %>% 
  mutate(cities_can_mex = abs(canada_dist - mexico_dist))

equidistant = cities_dist_eq %>% 
  filter(cities_can_mex <= 100)

top5_eq = slice_max(equidistant, population.x, n = 5)

ggplot() +
  geom_sf(data = conus, color = "black") +
  geom_sf(data = cities_dist_eq, size = 0.1) +
  geom_sf(data = top5_eq, color = "darkgreen") +
  gghighlight(cities_can_mex <= 100) +
  ggrepel::geom_label_repel(
    data = top5_eq,
    aes(label = city.x, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Equidistant Cities") + 
  ggthemes::theme_map()

Question 4

# 4.1 - Quantifying border zone

cities_dist_100 = cities_dist_USA %>% 
  filter(border_dist <= 160)

cities_dist_100_out = length(cities_dist_100$city)

pop_cities_dist_100 = sum(cities_dist_100$population)

pop_cities = sum(cities$population)

percent_pop_100 = pop_cities_dist_100 / pop_cities * 100

knitr::kable(tibble(cities_dist_100_out, pop_cities_dist_100, percent_pop_100), caption = "Cities Within 100 Miles of the US Border",
             col.names = c("Number of Cities within 100 Miles",
                           "Number of People within 100 Mile Zone",
                           "Percentage of Population within 100 Mile Zone"))
Cities Within 100 Miles of the US Border
Number of Cities within 100 Miles Number of People within 100 Mile Zone Percentage of Population within 100 Mile Zone
11958 259882582 65.01944

The ACLU estimates that rougly 2/3 (67%) of Americans live within 100 miles of the border. The results I got, which indicate that 65% of people live in this zone, are consistent with the ACLU’s estimate.

# 4.2 - Mapping border zone

top10_border = slice_max(cities_dist_100, population, n = 10)

ggplot() +
  geom_sf(data = conus_states, color = "black") +
  geom_sf(data = cities_dist_USA, aes(color = border_dist), size = 0.1) +
  geom_sf(data = top10_border, color = "grey") +
  scale_color_gradient(low = "orange", high = "darkred") +
  gghighlight(border_dist <= 160) +
  ggthemes::theme_map() +
  ggrepel::geom_label_repel(
    data = top10_border,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Cities Within Danger Zone",
       color = "Distance in km")

# Extra Credit

top_border_states = cities_dist_USA %>% 
  filter(border_dist <= 160) %>% 
  group_by(state_id) %>% 
  slice_max(population, n = 1)

ggplot() +
  geom_sf(data = conus_states, color = "black") +
  geom_sf(data = cities_dist_USA, aes(color = border_dist), size = 0.1) +
  geom_sf(data = top_border_states, color = "grey") +
  scale_color_gradient(low = "orange", high = "darkred") +
  gghighlight(border_dist <= 160) +
  ggthemes::theme_map() +
  ggrepel::geom_label_repel(
    data = top_border_states,
    aes(label = city, geometry = geometry),
    stat = "sf_coordinates",
    size = 3) +
  labs(title = "Cities Within Danger Zone",
       color = "Distance in km")